Discrete Strategies in Keyword Auctions and Their Inefficiency for Locally Aware Bidders

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We study formally discrete bidding strategies for the game induced by the Generalized Second Price keyword auction mechanism. Such strategies have seen experimental evaluation in the recent literature as parts of iterative best response procedures, which have been shown not to converge. We give a detailed definition of iterative best response under these strategies and, under appropriate discretization of the players’ strategy spaces we find that the discretized configurations space contains socially optimal pure Nash equilibria. We cast the strategies under a new light, by studying their performance for bidders that act based on local information; we prove bounds for the worst-case ratio of the social cost of locally stable configurations, relative to the socially optimum cost.

This work was partly funded by the EU FP7 Network of Excellence Euro-NF, through the specific joint research project AMESA. A full version with all omitted proofs is available at the authors’ homepages.